With the rise of internet technology and the growth of mobile communications, the global economy has undergone a significant transformation, shifting towards digital and soft markets. As a result, great efforts have been made to establish virtual marketplaces that provide customers with an exceptional shopping experience. One crucial aspect of this new paradigm is marketing, which has led to the emergence of a new stage known as E-marketing. In E-marketing, understanding customer behavior is of utmost importance. Marketing teams and companies are eager to gain insights into how different customer segments react to their products. Marketing strategies are now developed based on customer information such as financial status, location, age, gender, and more. As a result, the abundance of customer data generated by these new commerce technologies has surpassed the capabilities of traditional data analysis methods. To extract valuable knowledge from this vast amount of data, data mining technologies have come into play. Techniques such as clustering, classification, and prediction are utilized to mine marketing data and uncover hidden patterns and trends. The impact of data mining on E-marketing has been the subject of analysis in this study. A questionnaire-based review was conducted to collect the necessary data, which was then analyzed using SPSS 23 software. The study's results demonstrate that data mining can significantly enhance the performance of E-marketing by providing intelligent and efficient predictions of customer behaviour. Moreover, this technology offers similar advantages for end-customers as well. By leveraging the power of data mining, companies can gain valuable insights, tailor their marketing efforts, and ultimately provide better products and services to their customers in the digital marketplace.

Recent global trends related to the increasing use of e-commerce are becoming a challenge for courier transport especially in the last-mile process of delivering products to the final retail recipient. One of the delivery methods is the personal collection of the parcel in an automated post box, available 24/7 for the customer. This research aims to define the most important attributes of the courier services quality, including the delivery of parcels through automated sending and receiving parcel lockers, leveraging advanced technologies, data, and connectivity to enhance the quality of life, sustainability, and efficiency for city residents. The research was based on a preliminary selection of the most important features of parcel lockers’ service quality, which were extracted from the analysis of scientific literature and previous research. The analysis was carried out by conducting a survey among city parcel locker users that provided data coded according to the dimensions of the Kano model. This allowed to conclude that the location of parcel stations, ensuring improvements for the disabled, adjusting the size of the parcel to the size of the box, proper placement of the parcel in the box and a properly functioning dedicated application are the most important features in the process of automatic delivery of parcels to recipients in urban areas. This paper enriches the literature on customer service quality of self-service technologies for last-mile delivery with the use of automated parcel lockers.

: Airports are often the centers driving economic development of the local community in which they are located and have a significant impact on the national economy. Therefore, the infrastructural development of the airport is of great importance. On the other hand, passengers are becoming more experienced, more informed and more demanding in achieving their own satisfaction related to the level of quality of the service provided. The new airport infrastructure has an impact on improvement of customer experience, but with the assumption that certain physical and operational conditions are met. The research found that, in addition to the facilities that are part of the passenger operations, passengers pay significant attention to the commercial facilities, design and ambiance of the passenger terminal. It can be concluded that with the new airport infrastructure development such as passenger terminal, a wow effect at the customers will be achieved, but that only right design of ambient, simplified passenger flows and organization of commercial areas with a diverse offer and acceptable prices will ensure long term customer satisfaction and that the experience gap remains positive and sustainable.

This research focuses on the customer orientation of insurance brokers, whose activity is regulated by the Law of 26/2006 of July 17 on the mediation of private insurances and reinsurances. The goal is to ascertain whether the intermediation inherent in the insurance broker’s activity, which implies a customer-oriented service, entails a positive behaviour that transcends the immediate environment, reaching society. This study presents a comparative analysis between the insurance brokerage society, characterised by providing a personalised customer service, and banks’ advisory services on insurance. To this end, we study the evolution of the total volume of business and new production, compared for a portfolio of insurance products. The results presented in this research suggest that the customer values the advisory service provided by the broker. However, for a particular business segment in standardised insurance products and products related to banking assets, customers are more likely to resort to the bank’s services. In addition, the results indicate that the commission percentages applied by the entities operating in the banking insurance channel exceed those perceived by the insurance broker. With all this, intermediation in the development of the insurer’s activity can entail an ethical and social behaviour that involves customer-orientation and, possibly, social service, which does not always benefit the insurer.

In order to be able to face competition, thriving corporations have to be compelled to maintain an awfully smart relationship with their existing customers and additionally to be able to anticipate their future wants. Thus, corporations do not target customers as teams, however they’re attempting to focus on them as individuals. However, to be able to use this information, corporations have to be compelled to use promoting automation tools. Marketing Automation was an idea first introduced in 2001 by John D.C. Little in his presentation at the 5th Invitational Choice Symposium UC Berkeley 2001. This survey paper assesses prominent research on Marketing Automation and suggests how it can be modified to adapt to the current marketing scenario.

TThe number of supermarkets offering a grocery delivery has been increasing during the last years. Many studies deduce CO₂ emission savings using this concept. Since the delivery of groceries also consumes energy and produces emissions, break-even points can be calculated, from where the delivery has environmental advantages compared to the customer pickup. In this paper, influences of differing vehicle use on break-even points for savings of energy and CO₂ emissions are analyzed for the case of Haidhausen Süd, a city district of Munich in Germany. Internal combustion engine and electric vehicles are investigated to depict current as well as future trends. After an introduction to the used methodology, the potential to save energy and CO₂ emissions related to the delivery of groceries in the chosen district of Munich is evaluated. Afterwards, influences on the break even points are presented and discussed. As the results show, a delivery of groceries leads to energy and carbon dioxide savings in a wide range of private vehicle use for grocery shopping trips. Nevertheless, if the complete customer vehicle fleet is electrified, the use of delivery vehicles with an internal combustion engine can cause an additional environmental impact at the current modal split for shopping trips in Germany.

Social media platforms have become pivotal tools for small and medium-sized enterprises (SMEs), offering vast opportunities for enhanced organizational engagement. However, these platforms also present challenges such as data privacy concerns, feedback management, and content saturation. This systematic review critically evaluates the existing literature on the dual role of social media in fostering organizational engagement while addressing key barriers faced by SMEs. We systematically assessed 104 peer-reviewed articles sourced from Scopus, Web of Science, and Google Scholar, focusing on the impact of social media on marketing strategies and organizational outcomes in SMEs. The Newcastle-Ottawa Scale was used for quality assessment, and effect measures, including mean difference and odds ratio, were employed to evaluate performance metrics such as customer engagement, business performance, and long-term organizational impact. Key findings indicate that 74% of SMEs reported improvements in brand visibility, with customer engagement increasing by 65%. However, significant concerns were identified, with 45% of studies highlighting privacy issues and 52% addressing challenges in managing negative feedback. The review emphasizes that while social media can enhance market reach and customer interaction, its effectiveness largely depends on strategic content management and planning. This review provides actionable insights for SMEs aiming to optimize social media use, highlighting the need for future research to address privacy management and feedback strategies for sustained success.

This study investigates the transformative impact of technology adoption on retail marketing strategies, focusing on artificial intelligence (AI), big data analytics, augmented reality (AR), virtual reality (VR), mobile technology, and automated customer service solutions. Through qualitative research methods, including interviews and thematic analysis, insights were gathered from industry stakeholders across diverse retail sectors. The findings reveal that AI facilitates personalized marketing through data-driven insights, enhancing customer satisfaction and loyalty. Big data analytics enable retailers to forecast trends, optimize inventory, and tailor marketing strategies to consumer preferences effectively. AR and VR technologies enrich customer experiences by offering immersive and interactive shopping environments, bridging the gap between physical and digital retail spaces. Mobile technology supports omni-channel strategies, providing seamless integration and personalized interactions across platforms. The COVID-19 pandemic accelerated digital transformation in retail, emphasizing the resilience and adaptability of technology-driven strategies in navigating disruptions. AI-powered chatbots and virtual assistants streamline customer service operations, enhancing efficiency and customer satisfaction.

In this digital era, online learning and teaching is an important platform for college and university learners which required many technical facilities and in depth knowledge to have learning process effectively. Students and teachers in Higher Education Institutions (HEIs) were forced to grapple with the inevitability of shifting to online classes due to the advantages of effective distance learning or for large learning group. In the case of Oman, there have been some efforts to integrate alternative learning mechanisms such as online and mobile education in the past but not followed the scale in the post pandemic world. This study seeks to utilize the principles of Total Quality Management (TQM) through the implementation of Quality Function Deployment (QFD) as a way to better understand the experiences of Omani teachers and students from HEIs. A voice of customer from teachers and students have been collected and recorded. In this regard, 165 staff and 355 students from HEIs of Engineering participated in the survey. After the survey, a house of quality analysis was done to analyze the requirements based on how strongly they are related to the standard learning outcomes expected from HEIs in Oman. The results show that more attention is required in online education in the Sultanate of Oman before it is implemented as a major part in learning and teaching.

The recent past has witnessed a growing interest in technologies for creating chatbots. Advances in Large Language Models for natural language processing are underpinning rapid progress in chatbot development, and experts predict revolutionary changes in the labour market as many manual tasks are replaced by virtual assistants in a range of business functions. As the new technology becomes more accessible and advanced, more companies are exploring the possibilities of implementing virtual assistants to automate routine tasks and improve service. This article reports on qualitative inductive research undertaken within a chatbot development team operating in a major international enterprise. The findings identify critical success factors for chatbot projects, and, based on the in-depth case study, a model is put forward to aid the manageability of chatbot implementation. The presented model can serve as an exemplar guide for researchers and practitioners working on the design, development and implementation of virtual assistants. It is flexible and applicable in a wide range of business contexts, linking strategic business goals with execution steps. It is particularly applicable for teams with no experience of chatbot implementation, reducing uncertainty and managing decisions and risks throughout the project lifecycle, thereby increasing the likelihood of project success.

Optical networks offer a wide range of benefits to the telecommunication sector world- wide with its provision of higher bandwidth which leads to faster data speed, longer transmission distance, and improved latency. Currently, the complexity associated with advancements in optical networks poses problems to network flexibility, reliability, and quality of service. Over the years, many reviews and proposals have been implemented by several literatures to provide solutions for optical networks using software-defined networks and network service orchestrators. This paper reviews the significant challenges in current optical network applications, the various solutions rendered by software-defined networks as well as network service orchestration, the impediments, and gaps in these software – defined networks. This paper will go a step further to look into the various improvements and implementations of software-defined networks tailored to solve specific optical network problems. This paper further proposes a flexible orchestration architecture for software-defined networks for solving flexibility and scalability problems in optical networks. This proposal uses Open Network System (ONOS) SDN controller, leveraging on dockerisation as well as kubernetes clusterisation and orchestration. This solution presents a more flexible, reliable, customable, and higher quality of service which is an improvement upon current solutions in literature.

The modern economic landscape, now more competitive than ever, compels companies to create increasingly innovative, cutting-edge, and cost-effective products. In this regard, design and development phases play a crucial role, since they closely determine the final satisfaction of the customer. As a consequence, the need for a structured approach is evident, since it allows the companies to identify product key characteristics. With the purpose of creating a new product with an extended horizon to various markets, this work is based on the use of Design for Six Sigma (DFSS) methodology for the identification and optimization of Critical-To-Quality (CTQ) features, aiming at making the project as responsive as possible to customer needs. Two main themes are addressed. The first one is the analysis of the integrated product development process with the Six Sigma methodology for achieving design excellence; the second one is the application of the Identify phase of the IDOV (Identify, Design, Optimise, Validate) approach through a DFSS case study.

We discuss two queueing-inventory systems with catastrophes in the warehouse. Catastrophes occur according to Poisson process and upon arrival of a catastrophe all inventory in the system is instantly destroyed. But consumer customers in the system (in the server or in the buffer) continue still waiting for the replenishment of the stock. The arrivals of the consumer customers follow a Markovian Arrival Process (MAP) and they can be queued in an infinite buffer. Service time of a consumer customer follows a phase-type distribution. The system receives negative customers whose have Poisson flows to service facility and upon arrival of a negative customer one consumer customer is pushed out from the system, if any. One of two replenishment policies can be used in the system: either (s,S) or (s,Q). If upon arrival of the consumer customer, the inventory level is zero, then according to the Bernoulli scheme, this customer is either lost (lost sale scheme) or join the queue (backorder sale scheme). The system is formulated by a four-dimensional continuous-time Markov chain. Steady state distribution is obtained using the matrix-geometric method. A comprehensive numerical study is performed on the performance measures under various replenishment policies. Finally, an optimization study is presented.

E-commerce businesses employ recommender models to assist in identifying a personalized set of products for each visitor. To accurately assess the recommendations’ influence on customer clicks and buys, three target areas—customer behavior, data collection, user-interface —will be explored for possible sources of erroneous data. Varied customer behavior misrepresents the recommendations’ true influence on a customer due to the presence of B2B interactions and outlier customers. Non-parametric statistical procedures for outlier removal are delineated and other strategies are investigated to account for the effect of a large percentage of new customers or high bounce rates. Subsequently, in data collection we identify probable misleading interactions in the raw data, propose a robust method of tracking unique visitors, and accurately attributing the buy influence for combo products. Lastly, user-interface issues discuss the possible problems caused due to the recommendation widget’s positioning on the e-commerce website and the stringent conditions that should be imposed when utilizing data from the product listing page. This collective methodology results in an exact and valid estimation of the customer’s interactions influenced by the recommendation model in the context of standard industry metrics such as Click-through rates, Buy-through rates, and Conversion revenue.

Pharmacy personnel often answer telephones to respond to pharmacy customers (subjects) who received messages from automated systems. This research examines the communication process in terms of how users interact and engage with pharmacies after receiving automated messages. No study has directly addressed automated telephone calls and subjects’ interactions. The purpose of this study is to test the interpersonal communication (IC) process of uncertainty in subjects in receipt of automated telephone calls from pharmacies. Subjects completed a survey of validated scales for Satisfaction (S); Relevance (R); Quality (Q); Need for Cognitive Closure (NFC). Relationships between S, R, Q, NFC, and subject preference to an automated telephone call (ATC) were analyzed to determine whether subjects contacting pharmacies display information seeking behavior. This research demonstrates that seeking information occurs if subjects: are dissatisfied with the content of the ATC; perceive that the Q of the ATC is high; perceive that the Q of ATC is high, and like receiving the ATC or with high NFC, and do not like receiving ATCs. Other interactions presented complexities amongst uncertainty and tolerance of NFC within the IC process.

This qualitative research explores the transformative impact of technological innovations on retail marketing effectiveness. Through thematic analysis of interviews with industry professionals, the study identifies key themes including enhanced customer engagement, personalized marketing strategies driven by AI and machine learning, data-driven decision-making leveraging big data and analytics, the rise of e-commerce platforms, integration of mobile technologies, adoption of augmented reality (AR) and virtual reality (VR), development of omnichannel strategies, and implementation of loyalty programs. These themes illustrate how technology has reshaped retail marketing by enabling real-time customer interactions, personalized shopping experiences, and targeted marketing campaigns that enhance customer satisfaction and loyalty. The findings highlight the critical role of digital platforms like social media in fostering community engagement and brand loyalty. AI and machine learning facilitate personalized marketing efforts, tailoring product recommendations and enhancing customer experiences. Data-driven strategies optimize marketing ROI by providing insights into consumer behavior and market trends. E-commerce platforms expand market reach and streamline transactions, while mobile technologies and AR/VR innovations create immersive shopping experiences that captivate consumers. Omnichannel strategies integrate physical and digital channels, delivering seamless brand experiences and enhancing customer retention through CRM systems and loyalty programs. Looking ahead, retailers must navigate challenges such as rapid technological change, the need for continuous adaptation, and concerns about data privacy. By embracing technological advancements strategically and maintaining ethical standards, retailers can sustain competitive advantage, meet evolving consumer expectations, and drive growth in the digital era.

In the dynamic landscape of the telecommunications industry, understanding and mitigating customer churn is paramount for maintaining competitive advantage and sustaining revenue streams. This comprehensive literature review delves into the intricacies of customer churn prediction, a crucial aspect in fortifying the bond between telecom businesses and their customers. The review methodically analyzes 11 articles published between 2000 and March 2024, spotlighting the strategic role of Customer Relationship Management and the prevalence of high churn rates that necessitate a shift from customer acquisition to retention strategies. Furthermore, the review navigates through the challenges inherent in churn prediction, including the complexities of managing large, imbalanced, and noisy datasets and the intricacies involved in model selection and optimization. Despite these challenges, the paper highlights the superior capability of machine learning techniques in handling complex datasets to provide accurate predictions, albeit acknowledging their practical complexities. The main aim of the study is to provide an overview, serving as a knowledge base for researchers interested in machine learning techniques within the realm of telecommunications.

The use of Light Amplification by Stimulated Emission of Radiation (i.e., LASERs or lasers) by the U.S. Department of Defense is not new and includes laser weapons guidance, laser-aided measurements, even lasers as weapons (e.g., Airborne Laser). Lasers in support of telecommunications is also not new. The use of laser light in fiber optics shattered thoughts on communications bandwidth and throughput. Even the use of lasers in space is no longer new. Lasers are being used for satellite-to-satellite crosslinking. Laser communication can transmit orders-of-magnitude more data using orders-of-magnitude less power and can do so with minimal risk of exposure to the sending and receiving terminals. What is new is using lasers as the uplink and downlink between the terrestrial segment and the space segment of satellite systems. More so, the use of lasers to transmit and receive data between moving terrestrial segments (e.g., ships at sea, airplanes in flight) and geosynchronous satellites is burgeoning. This manuscript examines the technological maturation of employing lasers as the signal carrier for satellite communications linking terrestrial and space systems. The purpose of the manuscript is to develop key performance parameters (KPPs) to inform U.S. Department of Defense initial capabilities documents (ICDs) for near-future satellite acquisition and development. By appreciating the history and technological challenges of employing lasers rather than traditional radio frequency sources for satellite uplink and downlink signal carrier, this manuscript recommends ways for the U.S. Department of Defense to employ lasers to transmit and receive high bandwidth, large-throughput data from moving platforms that need to retain low probabilities of detection, intercept, and exploitation (e.g., carrier battle group transiting to a hostile area of operations, unmanned aerial vehicle collecting over adversary areas). The manuscript also intends to identify commercial sector early-adopter fields and those fields likely to adapt to laser employment for transmission and receipt.

Abstract:The digital landscape is rapidly reshaping under the influence of AI-powered cloud-based e-commerce platforms (PCEPs). These platforms leverage the transformative power of AI to personalize customer experiences, optimize pricing strategies, enhance security, and streamline operations, offering businesses a significant competitive edge. However, challenges surrounding data privacy, algorithmic bias, and potential job displacement raise crucial ethical questions regarding widespread AI adoption in e-commerce.This study delves into the untapped potential and ethical considerations of PCEPs, distinguishing itself by proposing practical strategies for responsible development and ethical implementation.Objectives: Investigate the transformative potential of PCEPs: Personalized product recommendations:Analyze effectiveness and potential bias. Dynamic pricing strategies:Explore impact on consumer fairness and market stability. Enhanced fraud detection:Evaluate accuracy and privacy implications. Optimized supply chain management:Assess efficiency gains and job displacement risks. Critically analyze the ethical considerations of AI in e-commerce: Data privacy:Assess current practices and develop mitigation strategies. Algorithmic bias:Identify potential sources and propose solutions for fairer decision-making. Job displacement:Evaluate impacts and propose reskilling initiatives. Propose comprehensive and practical strategies for responsible PCEP development and implementation: Transparency:Enhance user awareness and control over data usage. Fairness:Design AI systems to mitigate bias and uphold consumer rights. Accountability:Establish clear guidelines and oversight mechanisms for ethical AI development.Conclusion: While PCEPs offer a plethora of transformative benefits, their ethical implementation is paramount. By adhering to principles of transparency, fairness, and accountability, businesses can unlock the full potential of PCEPs while minimizing potential risks and shaping the future of online commerce in a sustainable and equitable manner

This paper explores the pivotal role of personalized product recommendations in enhancing the e-commerce experience. As online shopping becomes increasingly prevalent, the demand for tailored user experiences has surged, prompting the development of sophisticated recommendation systems. This study presents a comprehensive analysis of various methodologies employed to deliver personalized suggestions, including collaborative filtering, content-based filtering, and hybrid approaches. The implementation of a user-centric recommendation engine demonstrates significant improvements in user engagement, satisfaction, and conversion rates. Furthermore, the paper discusses the importance of real-time adaptation mechanisms and user feedback loops in optimizing recommendations. By providing insights into the challenges and solutions associated with recommendation systems, this research aims to equip e-commerce businesses with the tools necessary to leverage personalization effectively, ultimately leading to enhanced customer experiences and increased sales